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On maximum likelihood estimation in factor analysis: an algebraic derivation
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2009 (English)In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 89, no 6, 1260-1262 p.Article in journal (Refereed) Published
Abstract [en]

The maximum likelihood estimate in factor analysis is typically  obtained as the solution of the stationary point equation of the likelihood function. This type of derivation suffers from two problems: it is rather cumbersome and, in fact, it is incomplete as it does not include a proof that the so-obtained estimate is indeed a global maximum point of the likelihood function. In this note we present a simple algebraic derivation of the maximum likelihood estimate in factor models with spherical noise that applies to the general complex-valued data case.

Place, publisher, year, edition, pages
2009. Vol. 89, no 6, 1260-1262 p.
Keyword [en]
Factor analysis, Maximum likelihood
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-104505DOI: 10.1016/j.sigpro.2009.01.002ISI: 000264941900031OAI: oai:DiVA.org:uu-104505DiVA: diva2:219865
Available from: 2009-05-28 Created: 2009-05-28 Last updated: 2017-12-13Bibliographically approved

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Stoica, Peter

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